Postdoctoral Researcher focusing on privacy technologies and AI security at Fraunhofer Institute. Engaging in research, mentoring, and publishing in leading cryptography venues.
About the role
- Advanced AI Engineer at Honeywell designing AI algorithms and deploying solutions with a focus on Generative AI systems.
Responsibilities
- Design, develop, and optimize Generative AI and Agentic AI solutions for real-world, enterprise-grade applications.
- Build and orchestrate AI-powered agents and multi-agent systems using frameworks such as LangChain, LangGraph, and Databricks Mosaic AI Agent Framework.
- Architect and implement end-to-end AI pipelines, including data ingestion, feature engineering, model training, evaluation, and inference.
- Collaborate with product, data, platform, and business stakeholders to identify AI use cases and translate requirements into scalable AI solutions.
- Deploy and manage AI models and agents on cloud platforms (Azure, AWS, or GCP) using containerization (Docker/Kubernetes) and modern MLOps practices.
- Implement model monitoring, observability, and performance tracking to ensure accuracy, reliability, and responsible AI usage in production.
- Leverage MLflow for experiment tracking, model versioning, and lifecycle management.
- Utilize Databricks AI/ML Platform, including Unity Catalog, for governed data access, feature management, and secure AI deployments.
- Ensure AI systems meet enterprise standards for scalability, security, compliance, and maintainability.
- Stay current with emerging AI technologies, frameworks, and research, driving innovation and continuous improvement across AI solutions.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 6+ years of hands-on experience in AI/ML development, deployment, and productionization.
- Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and Scikit-learn.
- Proven hands-on experience building LLM-based applications and AI agents using LangChain, LangGraph, or similar frameworks.
- Experience deploying AI solutions on Azure, AWS, or GCP, with a solid understanding of cloud-native architectures.
- Strong foundation in data structures, algorithms, and software engineering best practices.
- Experience implementing MLOps pipelines, including CI/CD, model versioning, and monitoring.
- Strong knowledge of Generative AI models, including Large Language Models (LLMs) and diffusion-based models.
- Expertise in prompt engineering, retrieval-augmented generation (RAG), and tool-augmented LLM workflows.
- Experience designing Agentic AI architectures, autonomous workflows, and multi-agent systems.
- Hands-on experience with Databricks Mosaic AI, MLflow, and Unity Catalog for governed AI development.
- Familiarity with CI/CD pipelines for AI/ML solutions and infrastructure-as-code practices.
- Strong problem-solving skills with the ability to design scalable and maintainable AI systems.
- Excellent communication skills, with the ability to explain complex AI concepts to both technical and non-technical stakeholders.
Benefits
- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
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